To be clear, there are two different things here: The data about the league and the data about the player.
I don't think we have enough of *either* to be able to set a reasonable expectation for this player this year, unfortunately. If he plays 60 games there then we might have *something* but it's still going to be very wide, where, like, if he only has 20 points then that is bad and if he has 70 points then that is good but anything in between is going to be a shrug IMO.
And I don't think "quality" of the league is a one-dimensional metric as you want to boil it down to either, as we've discussed before.
Can we have any expectation based upon the data, reasonable or otherwise?
The contention here is about having a reasonable expectation with sufficient sample (ideal) versus a general expectation with wide room for error (it’s what we have).
I think that if there is enough data about the league to establish an equivalency, it is not an unknown variable. Perhaps a one-dimensional variable, yes, but still a variable nonetheless. Agree or disagree?
On the other hand, I do agree that there is an insufficient sample to make a reasonable assertion about the player. But this is going to be the case for every Russian player that transitions between leagues. Do we then just forget about projecting Russians at all? Even in a general sense, filled with error?
Mel, I think you know by now that I respect your intellect as a poster. I think it should be obvious. We’ve had tangent discussions about weighting equivalency markers differently, and about adjusting for improved league strength. It’s fascinating stuff and I like that we talk about it. Just know that before we delve further into this.